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About

Snowflake's Arctic Embed 2.0 introduces multilingual capabilities to its text embedding models, enhancing global-scale retrieval without compromising English performance or scalability. Building upon the robust foundation of previous releases, Arctic Embed 2.0 supports multiple languages, enabling developers to create stream-processing pipelines that incorporate neural networks and complex tasks like tracking, video encoding/decoding, and rendering, facilitating real-time analytics on various data types. The model leverages Matryoshka Representation Learning (MRL) for efficient embedding storage, allowing for significant compression with minimal quality degradation. This advancement ensures that enterprises can handle demanding workloads such as training large-scale models, fine-tuning, real-time inference, and high-performance computing tasks across diverse languages and regions.

About

EmbeddingGemma 2 is an open, lightweight multimodal embedding model designed to map text, code, images, video, and audio into a shared embedding space for search, retrieval, classification, routing, and RAG applications. Built on the Gemma 4 architecture and released under the Apache 2.0 license, it has 740 million parameters and is optimized for on-device inference. Its modular design can use as little as 270M parameters for text-only workloads, with optional vision and audio encoders for full multimodal support. Matryoshka Representation Learning lets developers reduce output vectors from 768 dimensions to 512, 256, or 128, lowering storage and memory requirements for local vector databases. The model supports an 8K-token context window and can process up to 5.5 minutes of audio, 29 images, 58 video frames, or interleaved combinations on local hardware.

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Not Supported
Cloud Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Not Supported
Cloud Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Audience

Global enterprises and developers in need of a solution to optimize their enhanced information retrieval and AI-driven applications

Audience

Developers and AI teams wanting to build private, efficient, on-device multimodal search, retrieval, RAG, and semantic indexing systems

Support

Phone Support Supported
24/7 Live Support Not Supported
Online Supported

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported

API

Offers API Not Supported

API

Offers API Supported

Screenshots and Videos

Screenshots and Videos

Pricing

$2 per credit
Free Version Not Supported
Free Trial Not Supported

Pricing

No information available.
Free Version Not Supported
Free Trial Not Supported

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation Supported
Webinars Supported
Live Online Supported
In Person Supported

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Company Information

Snowflake
Founded: 2012
United States
www.snowflake.com/en/engineering-blog/snowflake-arctic-embed-2-multilingual/

Company Information

Google
Founded: 1998
United States
blog.google/innovation-and-ai/technology/developers-tools/embeddinggemma-2/

Alternatives

Alternatives

txtai

txtai

NeuML

Categories

Embedding Models Supported

Categories

Embedding Models Supported

Integrations

OpenAI Supported
Snowflake Supported

Integrations

OpenAI Not Supported
Snowflake Not Supported
Claim Arctic Embed 2.0 and update features and information
Claim Arctic Embed 2.0 and update features and information
Claim EmbeddingGemma 2 and update features and information
Claim EmbeddingGemma 2 and update features and information